{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "\n",
    "from sklearn import datasets\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "from dnn_utils import initialize_parameters_deep, model_forward, compute_cost, model_backward, update_parameters, predict\n",
    "from plot_utils import plot_cost_accuracy, plot_decision_boundary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "X, y = datasets.make_moons(100000, noise=0.20)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_test, y_test, test_size=0.5, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x191d944b8c8>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_train[:1000,0], X_train[:1000,1], s=40, c=y_train[:1000], cmap=plt.cm.Spectral)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = X_train.T\n",
    "X_val = X_val.T\n",
    "X_test = X_test.T\n",
    "y_train = y_train.reshape((1, y_train.shape[0]))\n",
    "y_val = y_val.reshape((1, y_val.shape[0]))\n",
    "y_test = y_test.reshape((1, y_test.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def random_mini_batches(X, Y, mini_batch_size=32, seed=0):\n",
    "    np.random.seed(seed)            # To make your \"random\" minibatches the same as ours\n",
    "    m = X.shape[1]                  # number of training examples\n",
    "    mini_batches = []\n",
    "        \n",
    "    # Step 1: Shuffle (X, Y)\n",
    "    permutation = list(np.random.permutation(m))\n",
    "    shuffled_X = X[:, permutation]\n",
    "    shuffled_Y = Y[:, permutation].reshape((1,m))\n",
    "\n",
    "    # Step 2: Partition (shuffled_X, shuffled_Y). Minus the end case.\n",
    "    num_complete_minibatches = math.floor(m/mini_batch_size) # number of mini batches of size mini_batch_size in your partitionning\n",
    "    for k in range(0, num_complete_minibatches):\n",
    "        mini_batch_X = shuffled_X[:,k * mini_batch_size:(k + 1) * mini_batch_size]\n",
    "        mini_batch_Y = shuffled_Y[:,k * mini_batch_size:(k + 1) * mini_batch_size]\n",
    "        mini_batch = (mini_batch_X, mini_batch_Y)\n",
    "        mini_batches.append(mini_batch)\n",
    "    \n",
    "    # Handling the end case (last mini-batch < mini_batch_size)\n",
    "    if m % mini_batch_size != 0:\n",
    "        end = m - mini_batch_size * math.floor(m / mini_batch_size)\n",
    "        mini_batch_X = shuffled_X[:,num_complete_minibatches * mini_batch_size:]\n",
    "        mini_batch_Y = shuffled_Y[:,num_complete_minibatches * mini_batch_size:]\n",
    "        mini_batch = (mini_batch_X, mini_batch_Y)\n",
    "        mini_batches.append(mini_batch)\n",
    "    \n",
    "    return mini_batches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_model(X_train, y_train, X_val, y_val, layers_dims, \n",
    "                initial_learning_rate=0.01, batch_size=32, epochs=100, activation='tanh', \n",
    "                print_cost=False):\n",
    "    seed = 10\n",
    "    # keep track of cost\n",
    "    costs = []  \n",
    "    train_accs = []\n",
    "    val_accs = []\n",
    "    learning_rate = initial_learning_rate\n",
    "    # Parameters initialization.\n",
    "    parameters = initialize_parameters_deep(layers_dims)\n",
    "    # Loop (gradient descent)\n",
    "    for i in range(epochs):\n",
    "        seed = seed + 1\n",
    "        minibatches = random_mini_batches(X_train, y_train, batch_size, seed)\n",
    "        for minibatch in minibatches:\n",
    "            # Select a minibatch\n",
    "            (batch_X, batch_Y) = minibatch\n",
    "            \n",
    "            # Forward propagation: [LINEAR -> RELU]*(L-1) -> LINEAR -> SIGMOID.\n",
    "            AL, caches = model_forward(batch_X, parameters, activation)\n",
    "\n",
    "            # Compute cost.\n",
    "            cost = compute_cost(AL, batch_Y)\n",
    "\n",
    "            # Backward propagation.\n",
    "            grads = model_backward(AL, batch_Y, caches, activation)\n",
    "            \n",
    "            # Update parameters.\n",
    "            parameters = update_parameters(parameters, grads, learning_rate)\n",
    "        \n",
    "        # Annealing the learning rate\n",
    "        if (i + 1) % 10 == 0:\n",
    "                learning_rate = learning_rate * 0.63\n",
    "        \n",
    "        # Record cost, accuracy\n",
    "        y_train_pred = predict(X_train, parameters, activation)\n",
    "        train_acc = np.sum((y_train_pred == y_train) / X_train.shape[1])\n",
    "        y_val_pred = predict(X_val, parameters, activation)\n",
    "        val_acc = np.sum((y_val_pred == y_val) / X_val.shape[1])\n",
    "        costs.append(cost)\n",
    "        train_accs.append(train_acc)\n",
    "        val_accs.append(val_acc)        \n",
    "        # Print the cost every 10 training example\n",
    "        if print_cost and (i + 1) % 10 == 0:\n",
    "            template = \"Cost after iteration {}: {}, Learning rate: {}, Accuracy on train data: {}, Accuracy on validation data: {}\"\n",
    "            print(template.format(i + 1, cost, learning_rate, train_acc, val_acc))\n",
    "            \n",
    "\n",
    "    return parameters, costs, train_accs, val_accs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost after iteration 10: 0.49044041865731997, Learning rate: 0.0063, Accuracy on train data: 0.8697875000000003, Accuracy on validation data: 0.8679000000000003\n",
      "Cost after iteration 20: 0.33808820533826667, Learning rate: 0.003969, Accuracy on train data: 0.8755250000000002, Accuracy on validation data: 0.8746000000000003\n",
      "Cost after iteration 30: 0.09507164538728934, Learning rate: 0.0025004700000000003, Accuracy on train data: 0.8890875000000003, Accuracy on validation data: 0.8891000000000003\n",
      "Cost after iteration 40: 0.15558196501829483, Learning rate: 0.0015752961000000002, Accuracy on train data: 0.9519000000000002, Accuracy on validation data: 0.9516000000000004\n",
      "Cost after iteration 50: 0.09094337504584592, Learning rate: 0.0009924365430000002, Accuracy on train data: 0.9639375000000003, Accuracy on validation data: 0.9648000000000003\n",
      "Cost after iteration 60: 0.11298295037365985, Learning rate: 0.0006252350220900001, Accuracy on train data: 0.9667000000000003, Accuracy on validation data: 0.9680000000000003\n",
      "Cost after iteration 70: 0.1285740675995543, Learning rate: 0.00039389806391670006, Accuracy on train data: 0.9675250000000004, Accuracy on validation data: 0.9692000000000004\n",
      "Cost after iteration 80: 0.06862051565719704, Learning rate: 0.000248155780267521, Accuracy on train data: 0.9679125000000004, Accuracy on validation data: 0.9694000000000004\n",
      "Cost after iteration 90: 0.07312671994381705, Learning rate: 0.00015633814156853823, Accuracy on train data: 0.9681750000000003, Accuracy on validation data: 0.9697000000000003\n",
      "Cost after iteration 100: 0.04842639682757986, Learning rate: 9.849302918817909e-05, Accuracy on train data: 0.9683250000000003, Accuracy on validation data: 0.9699000000000003\n"
     ]
    }
   ],
   "source": [
    "layers_dims = [2, 3, 1]\n",
    "parameters, costs, train_accs, val_accs = build_model(X_train, y_train, X_val, y_val, layers_dims, epochs=100, print_cost=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_cost_accuracy(costs, train_accs, val_accs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_plot, y_plot = X_test[:, :1000].copy(), y_test[:, :1000].copy()\n",
    "plot_decision_boundary(lambda x: predict(x.T, parameters), X_plot, y_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9698000000000003"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred = predict(X_test, parameters)\n",
    "test_acc = np.sum((y_pred == y_test) / X_test.shape[1])\n",
    "test_acc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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